Abstract B15: Genomic and epigenomic events in arsenic-related lung squamous cell carcinomas from smokers and never smokers
Notice bibliographique
Résumé
Abstract Background: Arsenic is a well-known human carcinogen. An estimated of 160 million people (∼2% of total human population) are exposed to levels above the recommended threshold (10 μg/L) in Bangladesh, Taiwan, Mongolia, India, China, Argentina, Mexico, Canada, USA, and Chile, among others countries. Skin, bladder, liver, kidney and lungs are the main targets of arsenic carcinogenicity. Lung cancer (LC) is the most deadly form of neoplasia associated to arsenic ingestion. Additionally, lung squamous cell carcinomas (SqCC) occur at higher rates than other LC subtypes following exposure to this metalloid. Both genetic and epigenetic changes (some of them related to arsenic biotransformation) have been proposed to drive carcinogenesis; however, mechanisms are not fully understood. Here, we have compiled a panel of lung tumors from a population with chronic arsenic exposure, including a rare set of lung SqCC from patients who have never smoked. We analyzed to identify whole genome arsenic associated copy-number alterations (CNAs), copy-number variations (CNVs) and global DNA methylation changes. Methods: 52 lung SqCC were analyzed by whole-genome tiling path comparative genomic hybridization for CNA. Twenty-two were from arsenic exposed patients from Chile (10 never smokers and 12 smokers), and 30 additional non-exposed cases were from North America. In addition, 22 blood samples from healthy individuals from Northern Chile were examined to identify naturally occurring germline CNVs. Global DNA methylation analyses for 5 arsenic-exposed cases from never smokers were performed using Illumina's Infinium Human Methylation 450K array. Results: We identified arsenic related CNAs occurring in lung SqCC from patients with chronic exposure to this. The most recurrent events were represented by DNA losses at chromosomes 1q21.1, 7p22.3, 9q12, and 19q13.31. Also, we observed a single arsenic-associated DNA gain at 19q13.33, which contains genes related to single strand DNA breaks repair and neoplastic processes. Interestingly, alterations in this region have been reported to be more frequent among lung adenocarcinomas from never smokers compared with smokers. Additionally, distinctive DNA methylation patterns were associated to arsenic related lung SqCC from never smokers, indicating these changes can have an impact on carcinogenic mechanisms for this subgroup of lung tumors Conclusions: Our study provides insights into the molecular mechanisms of arsenic-induced lung SqCC. Moreover, findings specifically associated to cases among never smokers contribute to understand malignant events occurring in this rare subgroup of lung tumors. The unique and recurrent set of arsenic-associated genetic and epigenetic alterations suggests that this group of tumors may be considered as a distinct disease subclass. Finally, elucidation of the mechanisms underlying the initiation and promotion of carcinogenesis related to arsenic biotransformation processes is of foremost importance to the development of early detection protocols and treatment options for affected individuals.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».